A trajectory-informed model for detecting drug-drug-host interaction from real-world data.

ABSTRACT:

Objective

Adverse drug event (ADE) is a significant challenge to public health. Since data mining methods have been developed to identify signals of drug-drug interaction-induced (DDI-induced) or drug-host interaction-induced (DHI-induced) ADE from real-world data, we aim to develop a new method to detect adverse drug-drug interaction with a special awareness on patient characteristics.

Methods

We developed a trajectory-informed model (TIM) to identify signals of adverse DDI with a special awareness on patient characteristics (i.e., drug-drug-host interaction [DDHI]). We also proposed a study design based on an optimal selection of within-subject and between-subjects controls for detecting ADEs from real-world data. We analyzed a large-scale US administrative claims data and

SUBMITTER: Shi Y 

PROVIDER: S-EPMC12223795 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature